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          Redis缓存淘汰策略
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<p>Redis 使用的时内存空间来存储数据的，避免业务应用从后端数据库中读取数据，可以提升应用的响应速度。但是内存空间毕竟有限，随着我们存储数据的不断增长，要缓存的数据量越来越大，当超过了我们的内存大小时，该怎么办呢？</p>
</blockquote>
<p>Redis 4.0 之前一共实现了 6 种内存淘汰策略，在 4.0 之后，又增加了 2 种策略。我们可以按照是否会进行数据淘汰把它们分成两类：</p>
<ul>
<li>不进行数据淘汰的策略，只有 noeviction 这一种。</li>
<li>会进行淘汰的 7 种其他策略。会进行淘汰的 7 种策略，我们可以再进一步根据淘汰候选数据集的范围把它们分成两类：</li>
<li><ul>
<li>在设置了过期时间的数据中进行淘汰，包括 volatile-random、volatile-ttl、volatile-lru、volatile-lfu（Redis 4.0 后新增）四种。</li>
<li>在所有数据范围内进行淘汰，包括 allkeys-lru、allkeys-random、allkeys-lfu（Redis 4.0 后新增）三种。</li>
</ul>
</li>
</ul>
<p>具体如下：</p>
<ul>
<li>noeviction：直接返回错误，不进行数据淘汰</li>
<li>volatile-ttl：表示在设置可过期时间的键值对中，<strong>根据过期时间的先后进行淘汰数据，越早被过期的数据</strong>，越先被淘汰</li>
<li>volatile-random：从名字可以看出来，就是在设置了过期时间的键值对中，随机淘汰数据。</li>
<li>volatile-lru：根据 lru 算法进行数据的淘汰</li>
<li>volatile-lfu：根据lfu算法进行数据的淘汰</li>
<li>allkeys-random：在全部的键值对数据中，进行数据的随机淘汰。</li>
<li>allkeys-lru：在全部的键值对数据中，根据 lru 算法进行数据的淘汰。</li>
<li>allkeys-lfu：在全部的键值对数据中，根据 lfu 算法进行数据的淘汰。</li>
</ul>
<p><strong>默认情况下，Redis 在使用的内存空间超过 maxmemory 值时，并不会淘汰数据，也就是设定的 noeviction 策略。对应到 Redis 缓存，也就是指，一旦缓存被写满了，再有写请求来时，Redis 不再提供服务，而是直接返回错误。</strong></p>
<p>其中LRU算法的大家都比较熟悉了，LFU算法是在 LRU 算法的基础上，同时考虑了数据的访问时效性和数据的访问次数。参考链接<a target="_blank" rel="noopener" href="https://leetcode-cn.com/problems/lfu-cache/">LFU</a></p>

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